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Advanced integration of multimedia assistive technologies: A prospective outlook

机译:多媒体辅助技术的高级集成:前景展望

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In the recent years several studies on population ageing in the most advanced countries argued that the share of people older than 65 years is steadily increasing. In order to tackle this phenomena, a significant effort has been devoted to the development of advanced technologies for supervising the domestic environments and their inhabitants to provide them assistance in their own home. In this context, the present paper aims to delineate a novel, highly-integrated system for advanced analysis of human behaviours. It is based on the fusion of the audio and vision frameworks, developed at the Multimedia Assistive Technology Laboratory (MATeLab) of the Università Politecnica delle Marche, in order to operate in the ambient assisted living context exploiting audio-visual domain features. The existing video framework exploits vertical RGB-D sensors for people tracking, interaction analysis and users activities detection in domestic scenarios. The depth information has been used to remove the affect of the appearance variation and to evaluate users activities inside the home and in front of the fixtures. In addition, group interactions are monitored and analysed. On the other side, the audio framework recognises voice commands by continuously monitoring the acoustic home environment. In addition, a hands-free communication to a relative or to a healthcare centre is automatically triggered when a distress call is detected. Echo and interference cancellation algorithms guarantee the high-quality communication and reliable speech recognition, respectively. The system we intend to delineate, thus, exploits multi-domain information, gathered from audio and video frameworks each, and stores them in a remote cloud for instant processing and analysis of the scene. Related actions are consequently performed.
机译:近年来,对最先进国家的人口老龄化的几项研究认为,65岁以上人口的比例正在稳步增长。为了解决这种现象,已经致力于开发先进技术来监督家庭环境及其居民,以在他们自己的家中提供帮助。在这种情况下,本文旨在描述一种新颖的,高度集成的系统,用于对人类行为进行高级分析。它基于音频和视觉框架的融合,该框架是由Politecnica delle Marche大学的多媒体辅助技术实验室(MATeLab)开发的,目的是利用视听领域的功能在环境辅助的生活环境中进行操作。现有的视频框架利用垂直RGB-D传感器在家庭场景中进行人员跟踪,交互分析和用户活动检测。深度信息已用于消除外观变化的影响,并评估用户在家中和固定装置前的活动。此外,对小组互动进行监视和分析。另一方面,音频框架通过连续监视声学家庭环境来识别语音命令。另外,当检测到遇险呼叫时,会自动触发与亲戚或医疗中心的免提通信。回声和干扰消除算法分别保证了高质量的通信和可靠的语音识别。因此,我们打算描述的系统利用了从音频和视频框架中收集的多域信息,并将它们存储在远程云中,以便即时处理和分析场景。因此执行相关动作。

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